Development and Validation of Prognostic Nomograms to Predict Overall and Cancer-Specific Survival for Patients with Adenocarcinoma of the Urinary Bladder: A Population-Based Study.

BACKGROUNDS: Adenocarcinoma of the bladder (ACB) rarely occurs but is associated with poor outcome. We aim to establish reliable nomograms for estimating cancer-specific survival (CSS) and overall survival (OS) of ACB patients. METHODS: ACB patients were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2015). A total of 1,149 patients were randomly divided into training cohort (n = 692) and validation cohort (n = 457). Multivariate Cox proportional hazards regression models were employed to identify independent prognostic factors. Nomograms predicting OS and CSS were constructed utilizing screened factors. The performance of nomograms was internally and externally validated by calibration curves, the receiver operating characteristic (ROC) curves, concordance index (C-index), and decision curve analysis (DCA). RESULTS: OS nomogram incorporated age, race, histologic grade, American Joint Committee of Cancer (AJCC) stage, metastasis, surgery, chemotherapy, and tumor size. The C-indices were 0.754 (95% CI: 0.732-0.775) for training set and 0.743 (95% CI: 0.712-0.767) for validation set. Meanwhile, the calibration plots for 3- and 5-year OS displayed fine concordance between actual and predicted outcomes. In addition, higher areas under the curve (AUCs) were seen in training cohort (3-year: 0.799 vs. 0.630; 5-year: 0.797 vs. 0.648) and validation cohort (3-year: 0.802 vs. 0.662; 5-year: 0.752 vs. 0.660). Finally, DCA curves of the nomograms exhibited larger net benefits than AJCC stage. CSS nomogram showed similar results. CONCLUSION: Our study constructed and validated nomograms with improved discriminative abilities and clinical benefits to predict the survival outcomes of ACB patients. The models might assist clinicians in optimizing therapeutic management on individual levels.

Development and validation of a prognostic nomogram for predicting cancer-specific survival after radical cystectomy in patients with bladder cancer:A population-based study.

PURPOSE: To establish a prognostic model to estimate the cancer-specific survival (CSS) for urothelial carcinoma of bladder (UCB) patients after radical cystectomy (RC). METHODS: A total of 8650 candidates (2004-2011) obtained from the Surveillance, Epidemiology, and End Results (SEER) database were randomly split into development cohort (n = 4323) and validation cohort (n = 4327). We performed Cox regression analysis to identify prognostic factors and Kaplan-Meier analysis to assess survival outcome. A nomogram predicting CSS was constructed. Its performance was validated by calibration curves, the receiver operating characteristic (ROC) curves, concordance index (C-index), decision curve analysis (DCA), the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI). RESULTS: The nomogram incorporated marital status, T stage, N stage, tumor size, and chemotherapy. In validation cohort, C-index of the nomogram was 0.707. AUC of the nomogram and AJCC stage were 0.767 versus 0.674. Calibration plots for 3- and 5-year CSS displayed good concordance. DCA curves of the nomogram exhibited larger benefits than the AJCC stage. The NRI and IDI indicated the nomogram outperformed AJCC stage. CONCLUSIONS: We have established a prognostic nomogram with improved discriminative ability and clinical benefits for UCB patients after RC. The nomogram alongside an easy access web tool may assist clinicians in optimizing the postoperative management.